Tier 1 — Must-Have KPIs Directly anchored in the article's central thesis: lowest reconfiguration cost
KPI
What to monitor
What it may signal
Illustrative threshold
Review owner
Reconfiguration lead time
Days to shift X% of volume for a critical product family to an alternative supplier, site, or lane; trend quarter-on-quarter
Rising lead time = decaying optionality before disruption arrives; confirms whether the 'lowest reconfiguration cost' strategy is working in practice
🟢 ≤90 days for top 5 categories
🟡 Rising QoQ or 90–180 days
🔴 >180 days or no tested alternative exists
Supply chain strategy / network design
Optionality coverage ratio
% of revenue / critical SKUs covered by a pre-qualified second source, tested alternate lane, and approved plant footprint
Low or declining coverage = theoretical backup without usable optionality; concentration risk building silently
🟢 >80% of top-20 exposed categories fully covered
🟡 50–80%
🔴 <50% or coverage declining QoQ
Procurement / network design
Connector-country independence index
% of 'China+1' volume with genuine local value-add, non-China BOM, and independently qualified upstream supply; scored by corridor
Low scores = rerouting without genuine diversification; exposure to rules-of-origin challenge, transshipment scrutiny, or bloc-level restriction
🟢 >60% of diversified volume scores high on structural independence
🟡 30–60%
🔴 <30% or majority of volume in scrutinized connector corridors
Trade compliance / strategy
Data-foundation readiness
Time to produce a full-network scenario analysis; % master-data completeness; % of supplier/site/lane data digitally available
Long scenario-run time or data gaps = organization cannot execute scenario-based strategy; AI and automation investments will underdeliver
🟢 Scenario analysis within 5 working days, no manual data assembly
🟡 5–15 days
🔴 >15 days or requires ad-hoc external data collection
Technology / planning
Tier 2 — Strongly Add Genuine gaps in most corporate dashboards; well-supported by the analytical framework
KPI
What to monitor
What it may signal
Illustrative threshold
Review owner
Dual-stack / control-plane resilience
% of critical flows that can operate in an alternate compliant cloud/model/data environment; failover test success rate; cost of parallel stack maintenance
Low coverage = single point of failure in planning/compliance architecture; digital decoupling risk underestimated at the control-plane level
🟢 Critical flows covered by a tested alternate environment
🟡 Partial coverage, no tested failover
🔴 No alternate environment for any critical flow
Technology / legal / compliance
Cyber / decision-integrity
Planning-system downtime; model/data integrity incidents; supplier cyber exposure in critical tiers; DPP/traceability data exceptions; agentic AI decision audit rate
Incidents or downtime = supply chain continuity risk; adversarial exposure in AI-dependent planning; cybersecurity is a supply chain issue, not an IT side issue
🟢 Zero planning-system integrity incidents
🟡 Incidents isolated to non-critical flows
🔴 Integrity incident affecting a critical product category or planning output
IT / operations / risk
Exception load / planner firefighting index
Manual override rate; exception backlog aging; % of planners' time spent on expediting and firefighting
Rising exception load = organizational drift toward Stagnant & Exposed; AI/planning investment failing to absorb complexity; strong leading indicator for Scenario 4
🟢 Override rate declining QoQ, <20% of planner time on expediting
🟡 Override rate flat or rising
🔴 >40% of planner time on firefighting or backlog aging >30 days
Operations / planning
Water / power site exposure
% of critical sites and key suppliers in high water-stress or grid-constrained regions; days of utility disruption tolerance; share of AI/data-center-dependent operations in constrained regions
High exposure = unmodeled operational risk; AI infrastructure scaling constrained before competitive disadvantage is visible in service metrics
🟢 <20% of critical sites in high water/power-stress regions
🟡 20–40%
🔴 >40% or key AI infrastructure in constrained region with no contingency
Risk / sustainability / technology
Tier 3 — Sub-metrics Include with framing caveats; best treated as components within Tier 1–2 families
KPI
What to monitor
What it may signal
Illustrative threshold
Review owner
Time-to-recover / time-to-reroute
Days to restore target service after a node/lane disruption; days to approve and launch rerouting
Long recovery time = reactive, not proactive optionality; high reconfiguration cost even if alternatives theoretically exist
🟢 Rerouting approved and launched within 14 days
🟡 14–30 days
🔴 >30 days or no pre-approved rerouting protocol
Operations / supply chain strategy
Working capital efficiency vs. service level
Inventory days / safety stock growth paired with OTIF or fill rate; trend over 3–4 quarters
Rising working capital without service improvement = Scenario 4 drift signal; buffers accumulating reactively rather than strategically
🟢 Inventory days stable or declining with OTIF >95%
🟡 Inventory days rising without OTIF improvement
🔴 Rising inventory and declining OTIF simultaneously
Finance / operations
Circularity execution readiness
% SKU/BOM coverage with product-passport-ready traceability; return capture rate; remanufacturing yield; recycled-content secured vs. required by regulation
Low readiness = regulatory compliance risk and missed circularity economics; lagging behind EPR and DPP timelines
🟢 DPP-ready traceability for >80% of top-20 regulated SKUs
🟡 40–80%
🔴 <40% with regulatory deadline within 24 months
Sustainability / operations / legal
Supplier fragility / concentration
% spend in single-source positions; share of spend with financially weak suppliers; top-10 supplier concentration; capacity-utilization stress at critical suppliers
Rising concentration or supplier financial stress = failure appearing at balance-sheet level before service failure; stranding risk building
🟢 <30% of spend single-source, no top-20 supplier flagged financially weak
🟡 30–50% single-source
🔴 >50% single-source or critical supplier financial distress signal
Procurement / finance
Scenario 4 Stress-Test Tool — Days of Awareness / Survival / Recovery Run quarterly; reveals the gap between stated resilience and operational reality
Metric
What to measure
What it may signal
Illustrative threshold
Review owner
Days of Awareness
Days between first detectable signal of a disruption and management awareness; tests early-warning and monitoring maturity
Long awareness time = monitoring system is not operational; scenario signposts are not being watched; critical under Scenario 4 where drift is slow and signals are ambiguous
🟢 Disruption detected within 24–48 hours
🟡 2–7 days
🔴 >7 days or detected only after service impact
Strategy / risk / S&OP governance
Days of Survival
Days the company can maintain target service levels without the disrupted supplier, node, or lane; per critical product category
Short survival window = optionality has not been built in; reveals the gap between stated resilience strategy and operational reality; strongest Scenario 4 vulnerability signal
🟢 >90 days for Tier 1 categories
🟡 30–90 days
🔴 <30 days or unknown
Operations / supply chain strategy / finance
Days of Recovery
Days to restore target service levels after a disruption, measured from the point of awareness to full operational recovery; per critical node or lane
Long recovery time = reactive supply chain; high reconfiguration cost; reinforces the case for proactive optionality investment; use to stress-test against Scenario 4
🟢 Full recovery within 30 days
🟡 30–90 days
🔴 >90 days or no defined recovery protocol
Operations / supply chain strategy
Note on the Days of Awareness / Survival / Recovery framework: These three metrics are intentionally reactive — they quantify the cost of optionality not yet built. They complement the proactive Tier 1 and Tier 2 KPIs above. Companies with strong Tier 1 and Tier 2 scores will find, when they run the Days of Survival calculation, that their numbers are far better than competitors who have not made the same investments. Use the stress-test tool quarterly; use the Tier 1–2 indicators as the ongoing performance dashboard.